"Information on ordering products from websites" matching MCP servers:

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

8 standalone MCP servers for SMBs — Guardrails (prompt injection, PII, secrets detection), FinOps (AI cost tracking and budgets), Observability (agent tracing), Smart Router (17+ models, 9 providers), Trust Score (governance scoring 0-100), Memory (persistent agent memory), ThinkSecure (runtime security + SOC2/GDPR audit), and A2A Lite (agent-to-agent protocol). 37 tools total, TNC credits

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

An MCP server that lets Claude Code recall the context of past conversations from any project on demand.

Enables AI hosts to plan, draft, and check long-form novel chapters while honoring canon settings, character state, arcs, and check ordering, with approval-gated atomic commits. It keeps world, character, and chapter files as the human-editable source of truth, with snapshots and rollback for recovery.

A read-only MCP server providing tools to search and retrieve insurance product information, coverage details, and compare policies from a pre-built knowledge graph of Belgian insurance products, with verbatim citations from source PDFs.

Provides local, scoped access to DEVONthink 3 on macOS, enabling search, reading cited text, following references, and previewing document organization from an AI assistant.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

Provides persistent, searchable memory for AI agents, enabling them to retain, recall, and reflect on information across conversations.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Captures commitments from LLM conversations into a persistent local task list shown on an edge strip, with tools to add, list, and complete tasks.

An MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Enables building and managing knowledge workspaces with tools for ingesting content from text, clipboard, or URLs and searching organized knowledge bases. Supports multiple configurable workspaces with separate inbox and knowledge directories for structured information management.

Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.

A local MCP server that allows AI systems to search and retrieve information from a custom knowledge base generated from markdown files. It provides tools for natural language text search, category browsing, and specific content chunk retrieval.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

Enables querying and retrieving content from Confluence through CQL searches and page content fetching, allowing Claude to seamlessly access information stored in Confluence workspaces.

Enables interaction with the RAGFlow API to manage knowledge base datasets and conduct AI-driven chat sessions. Users can list datasets, create chat assistants, and retrieve or query information from specialized knowledge bases.

A Model Context Protocol server that enables AI assistants like Cursor to directly query and retrieve information from Dify knowledge bases through natural language.

Connect your MCP-compatible clients to Onyx AI knowledge bases for enhanced semantic search and chat capabilities. Retrieve relevant context from your documents seamlessly, enabling powerful interactions and comprehensive answers. Streamline knowledge management and improve access to information acr

Enables enterprise document retrieval using graph-based reasoning and knowledge graphs. Allows agents to search and extract information from scattered documents through structured entity and relationship extraction.

This project is based on the Knowledge Graph Memory Server from the MCP servers repository and retains its core functionality.

Enables seamless integration between Claude and Dry smartspaces, turning conversations into persistent, structured data by creating memories and querying information.

Enables AI agents to safely write to and read from persistent memory by validating every write through three independent consensus nodes, storing memories only on 2/3 agreement and quarantining poisoning attempts.

MCP server for the Postern personal context gateway, enabling agents to read and act on data from finance, health, mail, calendar, contacts, and home sources through a unified, cached interface.

Provides agents with durable, provenance-aware memory through tools for remembering, recalling, answering, and maintaining information, while structurally resisting injection and confabulation.